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Identifying excessive credit growth and leverage

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  • Alessi, Lucia
  • Detken, Carsten

Abstract

Unsustainable credit developments lead to the build-up of systemic risks to financial stability. While this is an accepted truth, how to assess whether risks are getting out of hand remains a challenge. To identify excessive credit growth and aggregate leverage we propose an early warning system, which aims at predicting banking crises. In particular, we use a modern classification tree ensemble technique, the “Random Forest”, and include (global) credit as well as real estate variables as predictors.

Suggested Citation

  • Alessi, Lucia & Detken, Carsten, 2018. "Identifying excessive credit growth and leverage," Journal of Financial Stability, Elsevier, vol. 35(C), pages 215-225.
    • Handle: RePEc:eee:finsta:v:35:y:2018:i:c:p:215-225
    DOI: 10.1016/j.jfs.2017.06.005
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    Full references (including those not matched with items on IDEAS)

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    Keywords

    Early warning systems; Banking crises; Credit; Macroprudential policy; Decision trees;

    JEL classification:

    • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
    • G01 - Financial Economics - - General - - - Financial Crises
    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • E61 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - Policy Objectives; Policy Designs and Consistency; Policy Coordination
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

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